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-100

102030405060708090

100

0 1 2 3 4 5 6 7 8 9 101112-10

0102030405060708090

100

0 1 2 3 4 5 6 7 8 9 101112-100

0

100

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0 1 2 3 4 5 6 7 8 9 101112

-100

0

100

200

0 1 2 3 4 5 6 7 8 9 101112

0

10

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Sep-12 Oct-12 Nov-12 Dec-12 Jan-13 Feb-13 Mar-13 Apr-13 May-13 Jun-13 Jul-13 Aug-130

10

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Sep-12 Oct-12 Nov-12 Dec-12 Jan-13 Feb-13 Mar-13 Apr-13 May-13 Jun-13 Jul-13 Aug-13

0

10000

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Sep

-11

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-11

No

v-1

1

Dec

-11

Jan

-12

Feb

-12

Mar

-12

Ap

r-1

2

May

-12

Jun

-12

Jul-

12

Au

g-1

2

Sep

-12

Oct

-12

No

v-1

2

Dec

-12

Jan

-13

Feb

-13

Mar

-13

Ap

r-1

3

May

-13

Jun

-13

Jul-

13

Au

g-1

3

Sep

-13 0

5000

10000

15000

20000

25000

30000

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40000

45000

50000

Sep-12 Oct-12 Nov-12 Dec-12 Jan-13 Feb-13 Mar-13 Apr-13 May-13 Jun-13 Jul-13 Aug-13 Sep-13

0

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1 2 3 4 5 6 7 8 9 10 11 12 13 14 150

100

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𝑀𝑆𝐸

Tried

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0.1

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0.9

1

0%

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A B C

% b

y va

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% b

y it

em

We first categorize the products into Runner, Repeater and Stranger according to Coefficient of Variation (COV). COV is calculated as standard deviation of forecasting error over average demand of product.

We then categorize according to monetary value. We adopted ABC analysis in which products were classified according to annual sales values.

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